code: def test_model_label_encoder(self):
      model = LabelEncoder()
      data = np.array([1, 4, 5, 2, 0, 2], dtype=np.int32)
      model.fit(data)
  
      torch_model = hummingbird.ml.convert(model, "torch")
      self.assertTrue(torch_model is not None)
      np.testing.assert_allclose(
          model.transform(data),
          torch_model.transform(data),
          rtol=1e-06,
          atol=1e-06,
      )
  
file_path: hummingbird/tests/test_sklearn_label_encoder_converter.py
imports: import unittest
  import numpy
  import torch
  from sklearn.preprocessing import LabelEncoder
  import hummingbird.ml
  from onnxconverter_common.data_types import Int32TensorType
label_desc: Use image node_id 1 for calling the TestSklearnLabelEncoderConverter obj's underlying member method code with example usage: obj.test_model_label_encoder() without return types